{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# LASER-embed tweets' texts"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Setup"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Load required modules"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "t6EV0T95rxhN"
      },
      "outputs": [],
      "source": [
        "import os\n",
        "from datetime import datetime\n",
        "import csv\n",
        "from laserembeddings import Laser"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Helper function"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "KqdLEhY8wkC1"
      },
      "outputs": [],
      "source": [
        "def chunk(x, n):\n",
        "    \"\"\"Yield successive n-sized chunks from lst.\"\"\"\n",
        "    # print(\"call `chunk()`\")\n",
        "    for i in range(0, len(x), n):\n",
        "        yield x[i:i + n]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Download LASER model files (if not yet available):"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {},
      "outputs": [],
      "source": [
        "if 'bilstm.93langs.2018-12-26.pt' not in os.listdir(Laser.DATA_DIR):\n",
        "    !python -m laserembeddings download-models\n",
        "    "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "cosGcLzpwm_P"
      },
      "outputs": [],
      "source": [
        "from types import SimpleNamespace\n",
        "\n",
        "args = SimpleNamespace()\n",
        "# we use a \"test\" file with only a sample if 5000 tweets in different languages\n",
        "args.inpath =  './../../data/testdata/test_tweets.csv'\n",
        "args.outpath = './../../data/intermediate/embeddings/test_tweet_laser_embeddings.tab'\n",
        "args.delim = ','\n",
        "args.quote = '\"'\n",
        "args.append = False\n",
        "args.overwrite = False\n",
        "args.chunksize = 1000"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "VmGAH1p1yFep"
      },
      "outputs": [],
      "source": [
        "if not os.path.exists(args.inpath):\n",
        "  raise ValueError(\"string passed to argument -i '%s' is not a valid file path.\" % args.inpath)\n",
        "\n",
        "if not os.path.isdir(os.path.dirname(args.outpath)):\n",
        "  raise ValueError(\"string passed to argument -o '%s' is not a valid directory path.\" % args.outpath)\n",
        "\n",
        "if args.append and args.overwrite:\n",
        "  raise ValueError(\"cannot both overwrite and append. Set either --append or --overwrite. \")\n",
        "\n",
        "if os.path.exists(args.outpath) and not args.append and not args.overwrite:\n",
        "  raise ValueError(\"File '%s' already exists. Set either --append or --overwrite.\" % args.outpath)\n",
        "\n",
        "write_mode = \"appended\" if args.append else \"written\""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "CushY1PmyURC"
      },
      "outputs": [],
      "source": [
        "# read-in CSV\n",
        "texts_dict = dict()\n",
        "with open(args.inpath, 'r') as infile:\n",
        "  data = csv.DictReader(infile, delimiter=args.delim, quotechar=args.quote)\n",
        "  n = 0\n",
        "  for r in data:\n",
        "    n += 1\n",
        "    lang = r.pop('lang')\n",
        "    if lang not in texts_dict:\n",
        "      texts_dict[lang] = [dict(r)]\n",
        "    else:\n",
        "      texts_dict[lang].append(dict(r))\n",
        "\n",
        "del data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZpIs4fa2yZgQ",
        "outputId": "f5ee3e61-d805-4ff5-db5b-0bd184c5a476"
      },
      "outputs": [],
      "source": [
        "# # print language counts\n",
        "# {l: len(d) for l, d in texts_dict.items()}"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "j6Kr389ZS9Cs"
      },
      "outputs": [],
      "source": [
        "# instantiate the LASER embedding model\n",
        "laser = Laser()"
      ]
    },
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      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "2023-10-26 11:51:04: Embedding 5000 texts in 21 different languages.\n",
            "2023-10-26 11:51:04: Embedding 1626 'es' texts in 2 chunk(s).\n",
            "2023-10-26 11:53:10: Embedding 40 'und' texts in 1 chunk(s).\n",
            "2023-10-26 11:53:12: Embedding 364 'fr' texts in 1 chunk(s).\n",
            "2023-10-26 11:53:41: Embedding 444 'de' texts in 1 chunk(s).\n",
            "2023-10-26 11:54:17: Embedding 134 'el' texts in 1 chunk(s).\n",
            "2023-10-26 11:54:29: Embedding 607 'en' texts in 1 chunk(s).\n",
            "2023-10-26 11:55:19: Embedding 526 'nl' texts in 1 chunk(s).\n",
            "2023-10-26 11:56:09: Embedding 151 'fi' texts in 1 chunk(s).\n",
            "2023-10-26 11:56:25: Embedding 124 'no' texts in 1 chunk(s).\n",
            "2023-10-26 11:56:36: Embedding 209 'ca' texts in 1 chunk(s).\n",
            "2023-10-26 11:57:09: Embedding 184 'it' texts in 1 chunk(s).\n",
            "2023-10-26 11:57:28: Embedding 48 'eu' texts in 1 chunk(s).\n",
            "2023-10-26 11:57:33: Embedding 212 'sv' texts in 1 chunk(s).\n",
            "2023-10-26 11:57:53: Embedding 136 'da' texts in 1 chunk(s).\n",
            "2023-10-26 11:58:07: Embedding 183 'pt' texts in 1 chunk(s).\n",
            "2023-10-26 11:58:25: Embedding 6 'cy' texts in 1 chunk(s).\n",
            "2023-10-26 11:58:26: Embedding 1 'tl' texts in 1 chunk(s).\n",
            "2023-10-26 11:58:26: Embedding 2 'ht' texts in 1 chunk(s).\n",
            "2023-10-26 11:58:27: Embedding 1 'tr' texts in 1 chunk(s).\n",
            "2023-10-26 11:58:27: Embedding 1 'et' texts in 1 chunk(s).\n",
            "2023-10-26 11:58:27: Embedding 1 'is' texts in 1 chunk(s).\n",
            "2023-10-26 11:58:27: LASER embdeddings TSV written to path './../../data/intermediate/embeddings/tweet_laser_embeddings.tab'\n"
          ]
        }
      ],
      "source": [
        "print(f\"{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}: Embedding {n} texts in {len(texts_dict)} different languages.\")\n",
        "\n",
        "# if all sentences are in the same language:\n",
        "\n",
        "if not args.append:\n",
        "  with open(args.outpath, 'w+') as outfile:\n",
        "    header = ['id', 'lang', 'text'] + ['e%04d' % e for e in range(1, 1025)]\n",
        "    outfile.write('\\t'.join(header))\n",
        "    outfile.write('\\n')\n",
        "\n",
        "# iterate over language subsets\n",
        "for lang, data in texts_dict.items():\n",
        "  c = len(data)\n",
        "\n",
        "  # create ids and texts chunks\n",
        "  ids_chunks = list(chunk([d['id'] for d in data], args.chunksize))\n",
        "  texts_chunks = list(chunk([d['text'] for d in data], args.chunksize))\n",
        "  n_chunks = len(ids_chunks)\n",
        "  print(f\"{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}: Embedding {c} '{lang}' texts in {n_chunks} chunk(s).\")\n",
        "\n",
        "  cnk = 0\n",
        "  for i in range(n_chunks):\n",
        "\n",
        "    ids = ids_chunks.pop(0)\n",
        "    texts = texts_chunks.pop(0)\n",
        "    cnk += 1\n",
        "    # get embeddings\n",
        "    failure = False\n",
        "    try:\n",
        "      em = laser.embed_sentences(texts, lang = lang)\n",
        "    except Exception as e:\n",
        "      failure = True\n",
        "      print(f\"{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}: WARNING: cannot embed texts with language code '{lang}' (chunk {chunk}). Reason: {str(e)}\")\n",
        "    else:\n",
        "      with open(args.outpath, 'a+') as outfile:\n",
        "        for i in range(len(ids)):\n",
        "          base = [ids[i], lang, repr(texts[i])]\n",
        "          if failure:\n",
        "            embedding = [''] * 1024\n",
        "          else:\n",
        "            embedding = [e for e in map(repr, list(em[i, ]))]\n",
        "          temp = base + embedding\n",
        "          outfile.write('\\t'.join(temp))\n",
        "          outfile.write('\\n')\n",
        "\n",
        "print(f\"{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}: LASER embdeddings TSV {write_mode} to path '{args.outpath}'\")\n"
      ]
    }
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